Photovoltaic power prediction method based on solar radiation climate characteristic recognition

Abstract

The invention relates to a photovoltaic power prediction method based on solar radiation climate characteristic recognition, which comprises the following steps: 1) defining a weather type index SCF,and classifying and dividing weather state data corresponding to different times according to the weather type index SCF; 2) respectively selecting a slope radiation model for each type of weather state data to predict slope incident total radiation; 3) constructing a photovoltaic cell model to predict the direct-current power generation power of the photovoltaic array; and 4) constructing an inverter model, and calculating according to the photovoltaic array direct-current power generation power prediction value to obtain photovoltaic array alternating-current power generation power, therebyfinishing photovoltaic power prediction. Compared with the prior art, the method has the advantages of flexible application scene, weather type recognition, accuracy improvement, power prediction error reduction and the like.

Description

technical field [0001] The invention relates to the field of photovoltaic power generation evaluation and prediction, in particular to a photovoltaic power prediction method based on solar radiation climate feature recognition. Background technique [0002] According to the statistics of the National Energy Administration, in 2019, the newly installed photovoltaic power generation capacity in the country was 30.11 million kilowatts, of which the newly installed photovoltaic power generation capacity was 17.91 million kilowatts; the newly installed photovoltaic photovoltaic capacity was 12.2 million kilowatts, a year-on-year increase of 41.3%. The cumulative installed capacity of photovoltaic power generation reached 204.3 million kilowatts, a year-on-year increase of 17.3%, of which concentrated photovoltaic power was 141.67 million kilowatts, a year-on-year increase of 14.5%; distributed photovoltaic power generation was 62.63 million kilowatts, a year-on-year increase of 24...

AI Technical Summary

Problems solved by technology

[0008] 1. The existing photovoltaic power prediction technology is difficult to apply to different locations, any inclination angle and azimuth (orientation)

[0009] 2. In the existing photovoltaic power prediction technology, the connection between the power prediction link and the radiation prediction link is not effective

[0010] 3. Most of the existing weather types are classified using a single index clarity index kt or modified clarity index kt’ or total cloud cover as the classification standard, ignoring the influence of other elements on weather types

[0011] 4. The existing inverter efficiency model, such as a simple constant model, has a large error in the case of low DC power input (corresponding to low solar radiation input)

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